Zilliant has helped B2B companies adopt data-driven price management for years. Through this experience, we have acquired a deep understanding of the key capabilities required to make it work.

Price Segmentation—The Foundation for Effective Price Decisions

Price segmentation leverages advanced pricing science to sift through volumes of historical pricing data and cull out price response patterns. The variations in price response are correlated with circumstances under which the deals were priced, and are used to establish differentiated, profit-maximizing pricing policies.

The central premise of price segmentation is intuitive—pricing should be consistent for similar deals. The breakthrough is that price segmentation quantifies similarity by empirically determining which deal circumstances affect price response. This quantitative understanding of what drives price outcomes makes it possible to benchmark prices against truly similar transactions. Benchmarking helps decision makers to understand and target the best (most profitable) prices that can likely be achieved for a given set of deal circumstances.

So what exactly are deal circumstances? In B2B, pricing outcomes reflect the combined effect of customer needs, seller motivations and competitive dynamics around each deal (i.e. quote, contract, or purchase agreement). While the exact influence of these factors on a deal is difficult to pinpoint, most can be inferred from the associated circumstances. Some examples of deal circumstances that commonly influence pricing outcomes include customer attributes such as industry and geography; product attributes such as lifecycle stage, degree of commoditization and end-use; and order attributes such as level of competition, order size and sales channel.

Each distinct combination of deal attributes determined to affect outcomes defines a price segment. Price segments are used to cluster transactions that share customer, product and order attributes, and therefore should produce similar price outcomes. They contain the best subset of historical pricing data for benchmarking and targeting prices for new deals with matching circumstances. Ultimately, price segments are the scientific foundation for data-driven price analysis, setting and execution.

Price Analysis—How and Where to Improve Profitability

Accurately assessing the pricing and margin characteristics of customers, products, and deals is a complex challenge. This is complicated by the special terms, packaging, promotions, off-invoice adjustments and one-off costs that are common in B2B transactions.

Data-driven price analysis leverages price segmentation to overcome this challenge. It uses the price segments to group pricing and margin data for customers, products and channels, and produces rich insights into their relative performance against peer groups. This provides an actionable view of relative pricing and profitability, and allows pricing decision makers to quickly and easily identify areas ripe for pricing improvement.

Price Setting—Determining the Best Price

Many companies lack the tools and pricing insight needed to effectively align prices with costs, competition and other market dynamics, and to evaluate the financial impact of pricing on revenues and margins. In contrast, data-driven price setting leverages scientific price segmentation and optimization to determine pricing policies and targets. Prices are optimized to maximize total margin or revenue, while taking into account pricing strategies, market and customer constraints, and overall corporate objectives.

Quantitative, segment-specific price setting produces significantly higher gross margins than legacy, undifferentiated pricing.

Price Execution—Pricing Right on Every Deal

Just because optimal prices and margin targets are known does not guarantee they will be achieved in the market. With limited information, manual processes and wide discretion, typical price execution activities leak significant margin through excessive discounting, poor control and administrative errors.

In contrast, companies that adopt a more quantitative, disciplined approach to price execution can eliminate unnecessary concessions and recapture lost profits without adversely affecting win rates. Through the combined use of quantitative benchmarks and end-to-end automation, data-driven price execution helps sales teams and pricing analysts to make more informed pricing decisions, ensure consistent and accurate quoting, and enforce key pricing policies company-wide.

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